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Publish WeightProgramBench: 317 training games and 5 held-out MinAtar tasks
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from dataclasses import dataclass
import math
import numpy as np
HORIZON = 400
FRAMES_PER_STEP = 4
PLAYER_X = 35
GROUND = 80
JUMP_DURATION = 30
@dataclass
class Enemy:
x: float
y: float
size: float
class BladeDancerEnvironment:
score_cap = 100
def __init__(self, sticky_action_prob: float = 0.1, horizon: int = HORIZON):
self.sticky_action_prob = sticky_action_prob
self.horizon = min(horizon, HORIZON)
self.seed(0)
self.reset()
def seed(self, seed: int) -> None:
self.random = np.random.default_rng(seed)
def reset(self) -> None:
self.steps = 0
self.pressed = self.terminal = False
self.jump_ticks = 0.0
self.y = float(GROUND)
self.angle = math.pi / 2
self.length = 10.0
self.multiplier = 1
self.enemies: list[Enemy] = []
self.platforms = [(0.0, 200.0)]
@classmethod
def normalize_score(cls, score: float) -> float:
return min(max(score, 0), cls.score_cap) / cls.score_cap
def act(self, action: int) -> tuple[float, bool]:
if self.terminal:
return 0.0, True
pressed = self.pressed if self.random.random() < self.sticky_action_prob else action == 5
if pressed and not self.pressed and not self.jump_ticks:
self.jump_ticks = JUMP_DURATION
self.multiplier = 1
self.pressed = pressed
self.steps += 1
reward = 0
for _ in range(FRAMES_PER_STEP):
reward += self._advance_frame()
if self.terminal:
break
self.terminal |= self.steps >= self.horizon
return float(reward), self.terminal
def _sword_vector(self) -> tuple[float, float]:
return self.length * math.cos(self.angle), self.length * math.sin(self.angle)
def _advance_frame(self) -> int:
if self.jump_ticks:
self.jump_ticks = max(0, self.jump_ticks - (0.5 if self.pressed else 1))
progress = self.jump_ticks / JUMP_DURATION
self.y = GROUND - math.sin(progress * math.pi) * 30
self.angle = self.angle - 0.3 if self.jump_ticks else math.pi / 2
self.length = 8 + (1 - progress) * 22 if self.jump_ticks else 10
if not self.enemies or self.random.random() < 0.04:
if len(self.enemies) == 32:
self.enemies.pop(0)
self.enemies.append(Enemy(205, self.random.uniform(30, 75), self.random.uniform(3, 6)))
reward = 0
survivors = []
sword_x, sword_y = self._sword_vector()
sword_radius = 2.5 if self.jump_ticks else 1
for enemy in self.enemies:
enemy.x -= 1
dx, dy = enemy.x - PLAYER_X, enemy.y - (self.y - 4)
fraction = min(1, max(0, (dx * sword_x + dy * sword_y) / self.length**2))
distance = math.hypot(dx - fraction * sword_x, dy - fraction * sword_y)
radius = enemy.size / 2
if distance <= radius + sword_radius:
reward += self.multiplier
self.multiplier += 1
continue
if abs(dx) < 2 + radius and abs(enemy.y - self.y) < 4 + radius:
self.terminal = True
if enemy.x >= -10:
survivors.append(enemy)
self.enemies = survivors
self.platforms = [(left - 1, right - 1) for left, right in self.platforms if right >= 1]
end = self.platforms[-1][1]
if end < 200:
gap = self.random.uniform(15, 30) if self.random.random() < 0.32 else 0
length = self.random.uniform(30, 100) if gap else self.random.uniform(50, 150)
self.platforms.append((end + gap, end + gap + length))
if not self.jump_ticks and not any(left <= PLAYER_X <= right for left, right in self.platforms):
self.terminal = True
return reward
def state(self) -> np.ndarray:
state = np.zeros((10, 10, 6), dtype=bool)
row, column = int(self.y) // 10, PLAYER_X // 20
state[row, column, 0] = True
state[row, column, 4] = self.jump_ticks > 0
sword_x, sword_y = self._sword_vector()
for fraction in np.linspace(0, 1, 12):
y = int(self.y - 4 + fraction * sword_y) // 10
x = int(PLAYER_X + fraction * sword_x) // 20
state[y, x, 1] = True
for enemy in self.enemies:
if 0 <= enemy.x < 200:
state[int(enemy.y) // 10, int(enemy.x) // 20, 2] = True
for column in range(10):
x = 20 * column + PLAYER_X % 20
state[8, column, 3] = any(left <= x <= right for left, right in self.platforms)
state[9, 0, 5] = self.pressed
for row, value in enumerate((int(self.jump_ticks * 2), self.multiplier, self.steps)):
for bit in range(9):
state[row, bit, 5] = bool(value & (1 << bit))
return state